Results for “prompt-quality”

After a Content Factory run completes successfully, harvest prompts, character references, cost data, and quality scores; diff them against the canonical prompt_registry and character_identity store; open improvement PRs (prompt updates + new character references). Runs ONCE per successful run, then closes. Also files findings into a CF_IMPROVER_ISSUES.csv (Intelliverse audit framework pattern) for the librarian's weekly roll-up.

Provides guidance and code for production AI workflows including RAG pipelines, vector databases, embedding indexing, prompt engineering, cost estimation, semantic caching, and quality evaluation.